Machine Learning in Production
Completed by Colin Steel
December 31, 2024
11 hours (approximately)
Colin Steel's account is verified. Coursera certifies their successful completion of Machine Learning in Production
What you will learn
Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.
Optimize model performance and metrics by prioritizing disproportionately important examples that represent key slices of a dataset.
Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.
Skills you will gain
- Category: Data Quality
- Category: Data Validation
- Category: System Monitoring
- Category: Continuous Deployment
- Category: Continuous Monitoring
- Category: Machine Learning
- Category: Data Maintenance
- Category: Data Preprocessing
- Category: Applied Machine Learning
- Category: Application Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Model Optimization
